Potential aboveground biomass increase in Brazilian Atlantic Forest fragments with climate change

Fragmented tropical forest landscapes preserve much of the remaining biodiversity and carbon stocks. Climate change is expected to intensify droughts and increase fire hazard and fire intensities, thereby causing habitat deterioration, and losses of biodiversity and carbon stock losses. Understanding the trajectories that these landscapes may follow under increased climate pressure is imperative for establishing strategies for conservation of biodiversity and ecosystem services. Here, we used a quantitative predictive modelling approach to project the spatial distribution of the aboveground biomass density (AGB) by the end of the 21st century across the Brazilian Atlantic Forest (AF) domain. To develop the models, we used the maximum entropy method with projected climate data to 2100, based on the Intergovernmental Panel on Climate Change Representative Concentration Pathway (RCP) 4.5 from the fifth Assessment Report. Our AGB models had a satisfactory performance (area under the curve > 0.75 and p value < .05). The models projected a significant increase of 8.5% in the total carbon stock. Overall, the projections indicated that 76.9% of the AF domain would have suitable climatic conditions for increasing biomass by 2100 considering the RCP 4.5 scenario, in the absence of deforestation. Of the existing forest fragments, 34.7% are projected to increase their AGB, while 2.6% are projected to have their AGB reduced by 2100. The regions likely to lose most AGB—up to 40% compared to the baseline—are found between latitudes 13° and 20° south. Overall, although climate change effects on AGB vary latitudinally for the 2071–2100 period under the RCP 4.5 scenario, our model indicates that AGB stocks can potentially increase across a large fraction of the AF. The patterns found here are recommended to be taken into consideration during the planning of restoration efforts, as part of climate change mitigation strategies in the AF and elsewhere in Brazil.     

Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China

In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS‐II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET‐II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010–2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad‐leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad‐leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types.     

多气候情景下中国森林火灾风险评估

森林火灾风险主要取决于致灾因子、承灾体以及防灾减灾能力,综合评估和预测森林火灾风险是制定科学的林火管理政策的基础.本文基于经典自然灾害风险模型和可获取数据构建森林火灾风险评估模型与指标体系,评估过去和未来的森林火灾风险.未来气候情景数据包括RCP 2.6、RCP 4.5、RCP 6.0和RCP 8.5下5个全球气候模式(GFDL-ESM2M、HadGEM2-ES、IPSL-CM5A-LR、 MIROC-ESM-CHEM和NorESM1-M)日值数据.根据最高温度、最小相对湿度、平均风速和每日降水量分别计算1987—2050年历史观测数据和未来气候情景下各格点每日火险天气指数系统中各个指数.结果表明: 1987—2010年,森林火灾风险高和很高的区域分别占21.2%和6.2%,主要分布在大兴安岭和长白山地区、云南大部分区域和南方零散分布的区域.森林火灾可能性高和很高的区域主要分布在东北和西南地区,分别占森林面积的13.1%和4.0%.与观测时段相比,2021—2050年RCP 2.6、RCP 4.5、RCP 6.0和RCP 8.5情景下森林火灾可能性高和很高的区域分别增加0.6%、5.5%、2.3%和3.5%,华北地区增幅明显.气候变化引起的森林火灾高风险区域有些增加,RCP 8.5情景下增幅最明显(+1.6%).     

Pinus taeda forest growth predictions in the 21st century vary with site mean annual temperature and site quality

Climate projections from 20 downscaled global climate models (GCMs) were used with the 3‐PG model to predict the future productivity and water use of planted loblolly pine (Pinus taeda) growing across the southeastern United States. Predictions were made using Representative Concentration Pathways (RCP) 4.5 and 8.5. These represent scenarios in which total radiative forcing stabilizes before 2100 (RCP 4.5) or continues increasing throughout the century (RCP 8.5). Thirty‐six sites evenly distributed across the native range of the species were used in the analysis. These sites represent a range in current mean annual temperature (14.9–21.6°C) and precipitation (1,120–1,680 mm/year). The site index of each site, which is a measure of growth potential, was varied to represent different levels of management. The 3‐PG model predicted that aboveground biomass growth and net primary productivity will increase by 10%–40% in many parts of the region in the future. At cooler sites, the relative growth increase was greater than at warmer sites. By running the model with the baseline [CO₂] or the anticipated elevated [CO₂], the effect of CO₂ on growth was separated from that of other climate factors. The growth increase at warmer sites was due almost entirely to elevated [CO₂]. The growth increase at cooler sites was due to a combination of elevated [CO₂] and increased air temperature. Low site index stands had a greater relative increase in growth under the climate change scenarios than those with a high site index. Water use increased in proportion to increases in leaf area and productivity but precipitation was still adequate, based on the downscaled GCM climate projections. We conclude that an increase in productivity can be expected for a large majority of the planted loblolly pine stands in the southeastern United States during this century.     

气候变化背景下江西省林火空间预测

林火是森林生态系统中重要的干扰因子之一,深刻地影响森林景观结构和功能。在全球气候化背景下,揭示气候变化对林火空间分布格局的影响,可为林火管理和防火资源分配提供科学指导。因此,基于江西省2001—2015年MODIS火影像数据(MCD14ML)和年均气温、年均降水量、植被、地形、人口密度、距道路距离、距居民点距离7个因子数据,利用增强回归树模型:(1)分析林火发生影响因子的相对重要性及其边际效应;(2)将GFDL-CM3和GISS-E2-R气候变化模式中的年均气温和年均降水量作为未来的气象数据,在3个温室气体排放量情景(RCP2.6、RCP4.5、RCP8.5)下,对2050年(2041—2060的平均值)和2070年(2061—2080的平均值)江西省林火分布进行预测,生成林火发生概率图。并采用受试者工作特征(ROC曲线)和混淆矩阵评估模型预测的精度。研究结果表明:(1)年均气温和海拔与江西省林火发生的相关性较强,年均降水量、居民点距离、人口密度、道路距离与林火发生的相关性较弱,但是与林火发生密切相关的如降水、风速等也应重点关注;(2)训练数据(70%)和验证数据(30%)的AUC值(ROC曲线下面积值)均为0.736,混淆矩阵对火点预测的正确率为67.8%,表明模型能够较好地预测研究区林火的发生;(3)在RCP8.5排放情景中林火发生的增幅最明显,其增幅较大的区域由赣南向赣北移动;(4)未来2050年和2070年林火发生与当前气候(2001—2015年)下相比,赣州市、鹰潭市的增幅较为明显,其他区域不明显。江西省各林业管理部门要加强林火高发区及潜在发生区的森林监测和管理,加大防火宣传力度,提升民众的森林防火意识。     

Climate-based identification of suitable cropping areas for giant reed and reed canary grass on marginal land in Central and Southern Europe under climate change

Giant reed (GR) and reed canary grass (RCG) have emerged as promising perennial industrial crops for providing sustainable bioenergy from marginal land. However, there is great uncertainty among farmers and researchers about where these crops can be grown in the future due to climate change, which complicates a timely transition to a bioeconomy. Therefore, this study quantifies marginal land and suitable cropping areas for GR and RCG in Europe, as well as their overlap. To derive these areas, the present (1991–2020) and future (2071–2100, RCP8.5) growing degree days, growing season length, annual precipitation, and aridity index were analyzed using the E-OBS observational dataset and EURO-CORDEX regional climate simulations. The study concludes that while marginal land will decrease by ~18%, GR and RCG will profit from the changing European climate, increasing by ~24% and ~13%, respectively. Looking at regions of overlap between marginal land and the selected crops, a decrease of ~87% and an increase of ~462% is projected for RCG and GR, respectively. This is due to marginal land shifting southward, benefitting the warm-season grass GR, while RCG prefers cooler climates.     

Land suitability for energy crops under scenarios of climate change and land‐use

Bioenergy is expected to play a critical role in climate change mitigation. Most integrated assessment models assume an expansion of agricultural land for cultivation of energy crops. This study examines the suitability of land for growing a range of energy crops on areas that are not required for food production, accounting for climate change impacts and conservation requirements. A global fuzzy logic model is employed to ascertain the suitable cropping areas for a number of sugar, starch and oil crops, energy grasses and short rotation tree species that could be grown specifically for energy. Two climate change scenarios are modelled (RCP2.6 and RCP8.5), along with two scenarios representing the land which cannot be used for energy crops due to forest and biodiversity conservation, food agriculture and urban areas. Results indicate that 40% of the global area currently suitable for energy crops overlaps with food land and 31% overlaps with forested or protected areas, highlighting hotspots of potential land competition risks. Approximately 18.8 million km² is suitable for energy crops, to some degree, and does not overlap with protected, forested, urban or food agricultural land. Under the climate change scenario RCP8.5, this increases to 19.6 million km² by the end of the century. Broadly, climate change is projected to decrease suitable areas in southern regions and increase them in northern regions, most notably for grass crops in Russia and China, indicating that potential production areas will shift northwards which could potentially affect domestic use and trade of biomass significantly. The majority of the land which becomes suitable is in current grasslands and is just marginally or moderately suitable. This study therefore highlights the vital importance of further studies examining the carbon and ecosystem balance of this potential land‐use change, energy crop yields in sub‐optimal soil and climatic conditions and potential impacts on livelihoods.     

Ensemble projections elucidate effects of uncertainty in terrestrial nitrogen limitation on future carbon uptake

The magnitude of the nitrogen (N) limitation of terrestrial carbon (C) storage over the 21st century is highly uncertain because of the complex interactions between the terrestrial C and N cycles. We use an ensemble approach to quantify and attribute process‐level uncertainty in C‐cycle projections by analysing a 30‐member ensemble representing published alternative representations of key N cycle processes (stoichiometry, biological nitrogen fixation (BNF) and ecosystem N losses) within the framework of one terrestrial biosphere model. Despite large differences in the simulated present‐day N cycle, primarily affecting simulated productivity north of 40°N, ensemble members generally conform with global C‐cycle benchmarks for present‐day conditions. Ensemble projections for two representative concentration pathways (RCP 2.6 and RCP 8.5) show that the increase in land C storage due to CO₂ fertilization is reduced by 24 ± 15% due to N constraints, whereas terrestrial C losses associated with climate change are attenuated by 19 ± 20%. As a result, N cycling reduces projected land C uptake for the years 2006–2099 by 19% (37% decrease to 3% increase) for RCP 2.6, and by 21% (40% decrease to 9% increase) for RCP 8.5. Most of the ensemble spread results from uncertainty in temperate and boreal forests, and is dominated by uncertainty in BNF (10% decrease to 50% increase for RCP 2.6, 5% decrease to 100% increase for RCP 8.5). However, choices about the flexibility of ecosystem C:N ratios and processes controlling ecosystem N losses regionally also play important roles. The findings of this study demonstrate clearly the need for an ensemble approach to quantify likely future terrestrial C–N cycle trajectories. Present‐day C‐cycle observations only weakly constrain the future ensemble spread, highlighting the need for better observational constraints on large‐scale N cycling, and N cycle process responses to global change.     

大兴安岭人为火发生影响因素及气候变化下的趋势

我国重要的北方针叶林地区大兴安岭是林火高发地区.受气候变暖影响,该地区林火发生频率将会发生显著变化.模拟人为火的发生分布与影响因素之间的关系、加强气候变化下人为火的发生分布预测,对于林火管理和减少森林碳损失具有重要作用.本文采用点格局分析方法,基于大兴安岭1967—2006年的火烧数据,建立人为火空间分布与影响因素之间的关系模型,该模型以林火发生次数为因变量,选取非生物因子(年均温和降水量、坡度、坡向和海拔)、生物因子(植被类型)和人为活动因子(距离道路距离、距离居民点距离、道路密度)共9个因子为自变量.并采用RCP 2.6和RCP 8.5气候情景数据代替当前气候情景预测2050年大兴安岭人为火的空间分布状况.结果表明: 点格局模型能够较好地模拟人为火发生分布与空间变量的关系,可以预测未来气候下人为火的发生概率.其中,气候因子对人为火的发生具有明显的控制作用,植被类型、海拔和人为活动等因子对人为火的发生也具有重要影响.林火发生预测结果表明,未来气候变化下,南部地区的林火发生概率将进一步增加,北部和沿主要道路干线附近将成为新的人为火高发区.与当前相比,2050年大兴安岭人为火的发生概率将增加72.2%～166.7%.在未来气候情景下,人为火的发生更多受气候和人为活动因素的控制.     

The impact of climate change on the distribution of two threatened Dipterocarp trees

Two ecologically and economically important, and threatened Dipterocarp trees Sal (Shorea robusta) and Garjan (Dipterocarpus turbinatus) form mono‐specific canopies in dry deciduous, moist deciduous, evergreen, and semievergreen forests across South Asia and continental parts of Southeast Asia. They provide valuable timber and play an important role in the economy of many Asian countries. However, both Dipterocarp trees are threatened by continuing forest clearing, habitat alteration, and global climate change. While climatic regimes in the Asian tropics are changing, research on climate change‐driven shifts in the distribution of tropical Asian trees is limited. We applied a bioclimatic modeling approach to these two Dipterocarp trees Sal and Garjan. We used presence‐only records for the tree species, five bioclimatic variables, and selected two climatic scenarios (RCP4.5: an optimistic scenario and RCP8.5: a pessimistic scenario) and three global climate models (GCMs) to encompass the full range of variation in the models. We modeled climate space suitability for both species, projected to 2070, using a climate envelope modeling tool “MaxEnt” (the maximum entropy algorithm). Annual precipitation was the key bioclimatic variable in all GCMs for explaining the current and future distributions of Sal and Garjan (Sal: 49.97 ± 1.33; Garjan: 37.63 ± 1.19). Our models predict that suitable climate space for Sal will decline by 24% and 34% (the mean of the three GCMs) by 2070 under RCP4.5 and RCP8.5, respectively. In contrast, the consequences of imminent climate change appear less severe for Garjan, with a decline of 17% and 27% under RCP4.5 and RCP8.5, respectively. The findings of this study can be used to set conservation guidelines for Sal and Garjan by identifying vulnerable habitats in the region. In addition, the natural habitats of Sal and Garjan can be categorized as low to high risk under changing climates where artificial regeneration should be undertaken for forest restoration.     

Near‐future forest vulnerability to drought and fire varies across the western United States

Recent prolonged droughts and catastrophic wildfires in the western United States have raised concerns about the potential for forest mortality to impact forest structure, forest ecosystem services, and the economic vitality of communities in the coming decades. We used the Community Land Model (CLM) to determine forest vulnerability to mortality from drought and fire by the year 2049. We modified CLM to represent 13 major forest types in the western United States and ran simulations at a 4‐km grid resolution, driven with climate projections from two general circulation models under one emissions scenario (RCP 8.5). We developed metrics of vulnerability to short‐term extreme and prolonged drought based on annual allocation to stem growth and net primary productivity. We calculated fire vulnerability based on changes in simulated future area burned relative to historical area burned. Simulated historical drought vulnerability was medium to high in areas with observations of recent drought‐related mortality. Comparisons of observed and simulated historical area burned indicate simulated future fire vulnerability could be underestimated by 3% in the Sierra Nevada and overestimated by 3% in the Rocky Mountains. Projections show that water‐limited forests in the Rocky Mountains, Southwest, and Great Basin regions will be the most vulnerable to future drought‐related mortality, and vulnerability to future fire will be highest in the Sierra Nevada and portions of the Rocky Mountains. High carbon‐density forests in the Pacific coast and western Cascades regions are projected to be the least vulnerable to either drought or fire. Importantly, differences in climate projections lead to only 1% of the domain with conflicting low and high vulnerability to fire and no area with conflicting drought vulnerability. Our drought vulnerability metrics could be incorporated as probabilistic mortality rates in earth system models, enabling more robust estimates of the feedbacks between the land and atmosphere over the 21st century.     

Coral Reef Habitat Response to Climate Change Scenarios

Coral reef ecosystems are threatened by both climate change and direct anthropogenic stress. Climate change will alter the physico-chemical environment that reefs currently occupy, leaving only limited regions that are conducive to reef habitation. Identifying these regions early may aid conservation efforts and inform decisions to transplant particular coral species or groups. Here a species distribution model (Maxent) is used to describe habitat suitable for coral reef growth. Two climate change scenarios (RCP4.5, RCP8.5) from the National Center for Atmospheric Research’s Community Earth System Model were used with Maxent to determine environmental suitability for corals (order Scleractinia). Environmental input variables best at representing the limits of suitable reef growth regions were isolated using a principal component analysis. Climate-driven changes in suitable habitat depend strongly on the unique region of reefs used to train Maxent. Increased global habitat loss was predicted in both climate projections through the 21^st century. A maximum habitat loss of 43% by 2100 was predicted in RCP4.5 and 82% in RCP8.5. When the model is trained solely with environmental data from the Caribbean/Atlantic, 83% of global habitat was lost by 2100 for RCP4.5 and 88% was lost for RCP8.5. Similarly, global runs trained only with Pacific Ocean reefs estimated that 60% of suitable habitat would be lost by 2100 in RCP4.5 and 90% in RCP8.5. When Maxent was trained solely with Indian Ocean reefs, suitable habitat worldwide increased by 38% in RCP4.5 by 2100 and 28% in RCP8.5 by 2050. Global habitat loss by 2100 was just 10% for RCP8.5. This projection suggests that shallow tropical sites in the Indian Ocean basin experience conditions today that are most similar to future projections of worldwide conditions. Indian Ocean reefs may thus be ideal candidate regions from which to select the best strands of coral for potential re-seeding efforts.     

The impacts of climate change on thermal stratification and dissolved oxygen in the temperate,dimictic Mississippi Lake,Ontario

This study investigates and reports the climate change's effects on the Mississippi Lake thermal structure and dissolved oxygen (DO) for baseline (1986–2005) and future (2081–2100) periods. Future meteorological variables were derived from the second-generation Canadian Earth System Model (CanESM2) under three emission scenarios (RCP2.6, RCP4.5, and RCP8.5). The long-term lake inflow was modelled using the Thornthwaite monthly water balance model (TMWB) coupled with an Artificial Neural Network (ANN) to simulate the water level in the lake. Several methods were analyzed to assure the above is the best for estimating the water budget in this region. The water quality of Mississippi Lake was analyzed using a calibrated CE-QUAL-W2 model for the years 2017 and 2018. A major challenge in setting up the model was limitations in some essential water quality indicator inputs, which were estimated using reliable experimental relationships. Our results show that the baseline average surface water temperature of 14.6 °C would increase by 1.31 °C, 1.34 °C, and 2.69 °C under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. In contrast, the baseline average hypolimnetic DO of 7.1 mg/L would decrease by 1.4%, 6.2%, and 14.3% in RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. Such a rise in water temperature and the consequent diminishment of DO in deep waters would threaten the future sustainable growth of warm-water fish species in Mississippi lake.     

Fire Damage in Seasonally Flooded and Upland Forests of the Central Amazon

Neighboring upland and nutrient‐poor seasonally flooded Amazon forests were penetrated by a fire in 2009, providing a natural comparative experiment of fire damage for these widespread forest types. In upland, only 16 ± 10% (±2 SEM) of stems and 21 ± 8% of basal area were lost to fire, while seasonally flooded forest lost 59 ± 13% of stems and 57 ± 13% of basal area. Drier understory contributes to greater flammability. Much of the area occupied by seasonally flooded woody vegetation (>11.5 percent of the Amazon region) is vulnerable to fire due to high flammability and slow recovery.     

气候变化对我国南方人工林地上生物量影响的模拟研究——以会同生态站磨哨实验林场为例

全球气候变暖对陆地生态系统尤其是森林生态系统有着重要的影响,气温升高、辐射强迫的增强将显著改变森林生态系统的结构和功能.南方人工林作为我国森林的重要组成部分,对气候变化的响应日益强烈.为了探究未来气候情景下我国南方人工林对气候变化的响应,降低未来气候变化对人工林可能带来的损失,本研究采用3种最新的气候情景—典型浓度排放路径情景(RCP2.6情景、RCP4.5情景、RCP8.5情景)预估数据,应用生态系统过程模型PnET-Ⅱ和空间直观景观模型LANDIS-Ⅱ模拟2014—2094年间湖南省会同森林生态实验站磨哨实验林场森林的地表净初级生产力(ANPP)、物种建立可能性(SEP)和地上生物量的变化.结果表明: 不同森林类型的SEP和ANPP对气候变化的响应有明显的差异,各森林类型对气候变化的响应程度表现为: 对于SEP,在RCP2.6和RCP4.5情景下,人工针叶林＞天然阔叶林＞人工阔叶林;在RCP8.5情景下,天然阔叶林＞人工阔叶林＞人工针叶林.对于ANPP,在RCP2.6情景下,人工阔叶林＞天然阔叶林＞人工针叶林;在RCP4.5和RCP8.5情景下,天然阔叶林＞人工阔叶林＞人工针叶林.人工针叶林的地上生物量在2050年左右开始下降,天然阔叶林和人工阔叶林整体呈现上升趋势.2014—2094年,研究区地上总生物量在不同气候情景下增加幅度不同,RCP2.6情景下增加了68.2%,RCP4.5情景下增加了79.3%,RCP8.5情景下增加了72.6%.3种情景下的总地上生物量大小排序为: RCP4.5> RCP8.5> RCP2.6.我们认为,适当的增温将有助于未来研究区森林总地上生物量的积累,但过度的增温也可能会阻碍森林的生产和生态功能的持续发展.     

Climate warming feedback from mountain birch forest expansion: reduced albedo dominates carbon uptake

Expanding high‐elevation and high‐latitude forest has contrasting climate feedbacks through carbon sequestration (cooling) and reduced surface reflectance (warming), which are yet poorly quantified. Here, we present an empirically based projection of mountain birch forest expansion in south‐central Norway under climate change and absence of land use. Climate effects of carbon sequestration and albedo change are compared using four emission metrics. Forest expansion was modeled for a projected 2.6 °C increase in summer temperature in 2100, with associated reduced snow cover. We find that the current (year 2000) forest line of the region is circa 100 m lower than its climatic potential due to land‐use history. In the future scenarios, forest cover increased from 12% to 27% between 2000 and 2100, resulting in a 59% increase in biomass carbon storage and an albedo change from 0.46 to 0.30. Forest expansion in 2100 was behind its climatic potential, forest migration rates being the primary limiting factor. In 2100, the warming caused by lower albedo from expanding forest was 10 to 17 times stronger than the cooling effect from carbon sequestration for all emission metrics considered. Reduced snow cover further exacerbated the net warming feedback. The warming effect is considerably stronger than previously reported for boreal forest cover, because of the typically low biomass density in mountain forests and the large changes in albedo of snow‐covered tundra areas. The positive climate feedback of high‐latitude and high‐elevation expanding forests with seasonal snow cover exceeds those of afforestation at lower elevation, and calls for further attention of both modelers and empiricists. The inclusion and upscaling of these climate feedbacks from mountain forests into global models is warranted to assess the potential global impacts.     

Climatic thresholds shape northern high‐latitude fire regimes and imply vulnerability to future climate change

Boreal forests and arctic tundra cover 33% of global land area and store an estimated 50% of total soil carbon. Because wildfire is a key driver of terrestrial carbon cycling, increasing fire activity in these ecosystems would likely have global implications. To anticipate potential spatiotemporal variability in fire‐regime shifts, we modeled the spatially explicit 30‐yr probability of fire occurrence as a function of climate and landscape features (i.e. vegetation and topography) across Alaska. Boosted regression tree (BRT) models captured the spatial distribution of fire across boreal forest and tundra ecoregions (AUC from 0.63–0.78 and Pearson correlations between predicted and observed data from 0.54–0.71), highlighting summer temperature and annual moisture availability as the most influential controls of historical fire regimes. Modeled fire–climate relationships revealed distinct thresholds to fire occurrence, with a nonlinear increase in the probability of fire above an average July temperature of 13.4°C and below an annual moisture availability (i.e. P‐PET) of approximately 150 mm. To anticipate potential fire‐regime responses to 21st‐century climate change, we informed our BRTs with Coupled Model Intercomparison Project Phase 5 climate projections under the RCP 6.0 scenario. Based on these projected climatic changes alone (i.e. not accounting for potential changes in vegetation), our results suggest an increasing probability of wildfire in Alaskan boreal forest and tundra ecosystems, but of varying magnitude across space and throughout the 21st century. Regions with historically low flammability, including tundra and the forest–tundra boundary, are particularly vulnerable to climatically induced changes in fire activity, with up to a fourfold increase in the 30‐yr probability of fire occurrence by 2100. Our results underscore the climatic potential for novel fire regimes to develop in these ecosystems, relative to the past 6000–35 000 yr, and spatial variability in the vulnerability of wildfire regimes and associated ecological processes to 21st‐century climate change.     

The fate of Amazonian ecosystems over the coming century arising from changes in climate,atmospheric CO2, and land use

There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO₂ levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias‐corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land‐use change scenarios. We assess the relative roles of climate change, CO₂ fertilization, land‐use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO₂ fertilization will enhance vegetation productivity and alleviate climate‐induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land‐use change and climate‐driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO₂ impacts varies considerably, depending on both the climate and land‐use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors – climate change, CO₂ fertilization effects, fire, and land use – to the fate of the Amazon over the coming century.     

Climate change disrupts core habitats of marine species

Driven by climate change, marine biodiversity is undergoing a phase of rapid change that has proven to be even faster than changes observed in terrestrial ecosystems. Understanding how these changes in species composition will affect future marine life is crucial for conservation management, especially due to increasing demands for marine natural resources. Here, we analyse predictions of a multiparameter habitat suitability model covering the global projected ranges of >33,500 marine species from climate model projections under three CO₂ emission scenarios (RCP2.6, RCP4.5, RCP8.5) up to the year 2100. Our results show that the core habitat area will decline for many species, resulting in a net loss of 50% of the core habitat area for almost half of all marine species in 2100 under the high-emission scenario RCP8.5. As an additional consequence of the continuing distributional reorganization of marine life, gaps around the equator will appear for 8% (RCP2.6), 24% (RCP4.5), and 88% (RCP8.5) of marine species with cross-equatorial ranges. For many more species, continuous distributional ranges will be disrupted, thus reducing effective population size. In addition, high invasion rates in higher latitudes and polar regions will lead to substantial changes in the ecosystem and food web structure, particularly regarding the introduction of new predators. Overall, our study highlights that the degree of spatial and structural reorganization of marine life with ensued consequences for ecosystem functionality and conservation efforts will critically depend on the realized greenhouse gas emission pathway.     

Spatial patterns and drivers of fire occurrence and its future trend under climate change in a boreal forest of Northeast China

Understanding the spatial patterns of fire occurrence and its response to climate change is vital to fire risk mitigation and vegetation management. Focusing on boreal forests in Northeast China, we used spatial point pattern analysis to model fire occurrence reported from 1965 to 2009. Our objectives were to quantitate the relative importance of biotic, abiotic, and human influences on patterns of fire occurrence and to map the spatial distribution of fire occurrence density (number of fires occurring over a given area and time period) under current and future climate conditions. Our results showed human‐caused fires were strongly related to human activities (e.g. landscape accessibility), including proximity to settlements and roads. In contrast, fuel moisture and vegetation type were the most important controlling factors on the spatial pattern of lightning fires. Both current and future projected spatial distributions of the overall (human‐ + lightning‐caused) fire occurrence density were strongly clustered along linear components of human infrastructure. Our results demonstrated that the predicted change in overall fire occurrence density is positively related to the degree of temperature and precipitation change, although the spatial pattern of change is expected to vary spatially according to proximity to human ignition sources, and in a manner inconsistent with predicted climate change. Compared to the current overall fire occurrence density (median value: 0.36 fires per 1000 km² per year), the overall fire occurrence density is projected to increase by 30% under the CGCM3 B1 scenario and by 230% under HadCM3 A2 scenario in 2081–2100, respectively. Our results suggest that climate change effects may not outweigh the effects of human influence on overall fire occurrence over the next century in this cultural landscape. Accurate forecasts of future fire‐climate relationships should account for anthropogenic influences on fire ignition density, such as roads and proximity to settlements.